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Molecular simulations can provide microscopic insight into the physical andchemical driving forces of complex molecular processes. Despite continuedadvancement of simulation methodology, model errors may lead to inconsistenciesbetween simulated and reference (e.g., from experiments or higher-levelsimulations) observables. To bound the microscopic information generated bycomputer simulations within reference measurements, we propose a method thatreweights the microscopic transitions of the system to improve consistency witha set of coarse kinetic observables. The method employs the well-developedMarkov state modeling framework to efficiently link microscopic dynamics withlong-time scale constraints, thereby consistently addressing a wide range oftime scales. To emphasize the robustness of the method, we consider twodistinct coarse-grained models with significant kinetic inconsistencies. Whenapplied to the simulated conformational dynamics of small peptides, thereweighting procedure systematically improves the time scale separation of theslowest processes. Additionally, constraining the forward and backward ratesbetween metastable states leads to slight improvement of their relativestabilities and, thus, refined equilibrium properties of the resulting model.Finally, we find that difficulties in simultaneously describing both thesimulated data and the provided constraints can help identify specificlimitations of the underlying simulation approach.

Consistent interpretation of molecular simulation kinetics using Markov state models biased with external information